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fanfuhan OpenCV 教學066 ~ opencv-066-圖像形態學(開閉操作時候結構元素應用演示) 資料來源: https://fanfuhan.github.io/ https://fanfuhan.github.io/2019/04/20/opencv-066/ GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV OpenCV中圖像形態學開操作與閉操作，根據結構元素的不同可以實現不同的二值圖像處理效果，我們可以通過下面的結構元素對圖像進行開操作，提取二值圖像中水平與垂直線，這個方法比霍夫直線檢測要好用得多， 在一些應用場景中會特別有用，圖像分析、OCR佈局分析中形態學操作十分重要，我們通過兩個例子來說明開閉操作的作用。 1開操作提取水平線，實現填空題橫線位置提取 結構元素大小為20×1     步驟：         01.轉灰度         02.轉二值，可選降噪         03.形態學操作，提取(偵測/尋找/檢測)水平線         04.輪廓發現，確定位置 2閉操作實現不同層次的輪廓填充     結構元素分為三種：         矩形結構元素35×35大小         矩形結構元素30×30大小         圓形結構元素30×30大小 C++ #include #include using namespace std ; using namespace cv; void open_demo () ; void close_demo () ; /* *圖像形態學(開閉操作時候結構元素應用演示) */ int main () { //open_demo(); close_demo(); waitKey( 0 ); return 0 ; } void close_demo () { //讀取圖像 Mat src = imread( "../images/morph3.png" ); imshow( "input" , src); //二值圖像 Mat gray, binary; cvtColor(src, gray, COLOR_BGR2GRAY); threshold(gray, binary, 0 , 255 , THRESH_BINARY | THRESH_OTSU); imshow( "binary" , binary); //閉操作// Mat se = getStructuringElement(MORPH_ELLIPSE, Size(30, 30), Point(-1, -1)); //Mat se = getStructuringElement(MORPH_RECT, Size(30, 30), Point(-1 , -1)); //Mat se = getStructuringElement(MORPH_RECT, Size( 35 , 35 ), Point( -1 , -1 )); morphologyEx(binary, binary, MORPH_CLOSE, se); imshow( "close_demo rect=35,35 " , binary); } void open_demo () { //讀取圖像 Mat src = imread( "../images/fill.png" ); imshow( "input" , src); //二值圖像 Mat gray, binary; cvtColor(src, gray, COLOR_BGR2GRAY); threshold(gray, binary, 0 , 255 , THRESH_BINARY_INV | THRESH_OTSU); imshow( "binary" , binary); //開操作 Mat se = getStructuringElement(MORPH_RECT, Size( 25 , 1 ), Point( -1 , -1 )); morphologyEx(binary, binary, MORPH_OPEN, se); imshow( "open_op" , binary); //繪製填空位置 vector < vector > contours; vector hierarhy; findContours(binary, contours, hierarhy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point( -1 , -1 )); for ( size_t t = 0 ; t < contours.size(); t++) { Rect roi = boundingRect(contours[t]); roi.y = roi.y - 10 ; roi.height = 12 ; rectangle(src, roi, Scalar( 0 , 0 , 255 )); } //顯示結果 imshow( "open_demo" , src); } Python import cv2 as cv import numpy as np def open_demo () : src = cv.imread( "D:/images/fill.png" ) cv.namedWindow( "input" , cv.WINDOW_AUTOSIZE) cv.imshow( "input" , src) #圖像二值化 gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) ret, binary = cv.threshold(gray, 0 , 255 , cv.THRESH_BINARY_INV | cv.THRESH_OTSU) cv.imwrite( "D:/binary1.png " , binary) cv.imshow( "binary1" , binary) #開操作 se1 = cv.getStructuringElement(cv.MORPH_RECT, ( 20 , 1 ), ( -1 , -1 )) binary = cv.morphologyEx(binary, cv.MORPH_OPEN, se1) cv.imshow( "binary" , binary ) cv.imwrite( "D:/binary2.png" , binary) #提取輪廓 out, contours, hierarchy = cv.findContours(binary, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) for c in range(len(contours)): x, y, w, h = cv.boundingRect(contours[c] ) y = y - 10 h = 12 cv.rectangle(src, (x, y), (x+w, y+h), ( 0 , 0 , 255 ), 1 , 8 , 0 ) cv.imshow( " result" , src) def close_demo () : src = cv.imread( "D:/images/morph3.png" ) cv.namedWindow( "input" , cv.WINDOW_AUTOSIZE) cv.imshow( "input" , src) #圖像二值化 gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) ret, binary = cv.threshold(gray, 0 , 255 , cv.THRESH_BINARY | cv.THRESH_OTSU) #閉操作 se = cv.getStructuringElement(cv.MORPH_ELLIPSE, ( 15 , 15 ), ( -1 , -1 )) binary = cv.morphologyEx(binary, cv.MORPH_CLOSE, se) cv.imwrite( "D:/close .png" , binary) cv.imshow( "close" , binary) close_demo() cv.waitKey( 0 ) cv.destroyAllWindows()